{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:PE5RWAYYFEH3OMBT6FXMTFVEK2","short_pith_number":"pith:PE5RWAYY","canonical_record":{"source":{"id":"1601.04149","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-01-16T10:38:43Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"6fb72e91ece15a0f8def08a4580bfaada03c3c30750e0353c8adfd3c2da0ca87","abstract_canon_sha256":"d8e786c62bcef2e8a9118c733c03b0634f104493c1aa1d33737ac6faa69b6000"},"schema_version":"1.0"},"canonical_sha256":"793b1b0318290fb73033f16ec996a45690c9596323679085a82734a24da44b04","source":{"kind":"arxiv","id":"1601.04149","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1601.04149","created_at":"2026-05-18T01:17:24Z"},{"alias_kind":"arxiv_version","alias_value":"1601.04149v3","created_at":"2026-05-18T01:17:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.04149","created_at":"2026-05-18T01:17:24Z"},{"alias_kind":"pith_short_12","alias_value":"PE5RWAYYFEH3","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"PE5RWAYYFEH3OMBT","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"PE5RWAYY","created_at":"2026-05-18T12:30:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:PE5RWAYYFEH3OMBT6FXMTFVEK2","target":"record","payload":{"canonical_record":{"source":{"id":"1601.04149","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-01-16T10:38:43Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"6fb72e91ece15a0f8def08a4580bfaada03c3c30750e0353c8adfd3c2da0ca87","abstract_canon_sha256":"d8e786c62bcef2e8a9118c733c03b0634f104493c1aa1d33737ac6faa69b6000"},"schema_version":"1.0"},"canonical_sha256":"793b1b0318290fb73033f16ec996a45690c9596323679085a82734a24da44b04","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:24.761782Z","signature_b64":"m60pxpfJl+ymNY7tKPVq9kSspZLPgULsF2/F8jYxJqYhqfhNMcHNWfUfIs/s1AmZ5RFFANm1Q8lcldiRzKraAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"793b1b0318290fb73033f16ec996a45690c9596323679085a82734a24da44b04","last_reissued_at":"2026-05-18T01:17:24.761281Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:24.761281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1601.04149","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:17:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"djE+kxwhhNlzKvdjr5Ha5r5EEVwr09D5O/Etki+sxZQkFfi3vpbG/ydsWE/kB2u6+mSbxxm00kZnJw2SwK14Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T03:37:28.274046Z"},"content_sha256":"7b3f168d306f0511ae95ef59847c286f92d1c81ce3599b0f0a7cd14aa2493162","schema_version":"1.0","event_id":"sha256:7b3f168d306f0511ae95ef59847c286f92d1c81ce3599b0f0a7cd14aa2493162"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:PE5RWAYYFEH3OMBT6FXMTFVEK2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"$\\mathbf{D^3}$: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Ding Liu, Qing Ling, Shiyu Chang, Thomas S. Huang, Yingzhen Yang, Zhangyang Wang","submitted_at":"2016-01-16T10:38:43Z","abstract_excerpt":"In this paper, we design a Deep Dual-Domain ($\\mathbf{D^3}$) based fast restoration model to remove artifacts of JPEG compressed images. It leverages the large learning capacity of deep networks, as well as the problem-specific expertise that was hardly incorporated in the past design of deep architectures. For the latter, we take into consideration both the prior knowledge of the JPEG compression scheme, and the successful practice of the sparsity-based dual-domain approach. We further design the One-Step Sparse Inference (1-SI) module, as an efficient and light-weighted feed-forward approxim"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.04149","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:17:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0k83yoheecbZN7qzaLa1tmuMYvb9huuA+qQHwVJt3tvkhi6B3BBw4t1coUF4oik889VdrkCnRNFm6KnRJ9u1Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T03:37:28.274411Z"},"content_sha256":"7329158d3b904de36205eca822bab862ff8e2469c3e1fe87ec62e260372f9b6e","schema_version":"1.0","event_id":"sha256:7329158d3b904de36205eca822bab862ff8e2469c3e1fe87ec62e260372f9b6e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2/bundle.json","state_url":"https://pith.science/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-01T03:37:28Z","links":{"resolver":"https://pith.science/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2","bundle":"https://pith.science/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2/bundle.json","state":"https://pith.science/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PE5RWAYYFEH3OMBT6FXMTFVEK2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:PE5RWAYYFEH3OMBT6FXMTFVEK2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"d8e786c62bcef2e8a9118c733c03b0634f104493c1aa1d33737ac6faa69b6000","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-01-16T10:38:43Z","title_canon_sha256":"6fb72e91ece15a0f8def08a4580bfaada03c3c30750e0353c8adfd3c2da0ca87"},"schema_version":"1.0","source":{"id":"1601.04149","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1601.04149","created_at":"2026-05-18T01:17:24Z"},{"alias_kind":"arxiv_version","alias_value":"1601.04149v3","created_at":"2026-05-18T01:17:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.04149","created_at":"2026-05-18T01:17:24Z"},{"alias_kind":"pith_short_12","alias_value":"PE5RWAYYFEH3","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"PE5RWAYYFEH3OMBT","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"PE5RWAYY","created_at":"2026-05-18T12:30:39Z"}],"graph_snapshots":[{"event_id":"sha256:7329158d3b904de36205eca822bab862ff8e2469c3e1fe87ec62e260372f9b6e","target":"graph","created_at":"2026-05-18T01:17:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"In this paper, we design a Deep Dual-Domain ($\\mathbf{D^3}$) based fast restoration model to remove artifacts of JPEG compressed images. It leverages the large learning capacity of deep networks, as well as the problem-specific expertise that was hardly incorporated in the past design of deep architectures. For the latter, we take into consideration both the prior knowledge of the JPEG compression scheme, and the successful practice of the sparsity-based dual-domain approach. We further design the One-Step Sparse Inference (1-SI) module, as an efficient and light-weighted feed-forward approxim","authors_text":"Ding Liu, Qing Ling, Shiyu Chang, Thomas S. Huang, Yingzhen Yang, Zhangyang Wang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-01-16T10:38:43Z","title":"$\\mathbf{D^3}$: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.04149","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7b3f168d306f0511ae95ef59847c286f92d1c81ce3599b0f0a7cd14aa2493162","target":"record","created_at":"2026-05-18T01:17:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"d8e786c62bcef2e8a9118c733c03b0634f104493c1aa1d33737ac6faa69b6000","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-01-16T10:38:43Z","title_canon_sha256":"6fb72e91ece15a0f8def08a4580bfaada03c3c30750e0353c8adfd3c2da0ca87"},"schema_version":"1.0","source":{"id":"1601.04149","kind":"arxiv","version":3}},"canonical_sha256":"793b1b0318290fb73033f16ec996a45690c9596323679085a82734a24da44b04","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"793b1b0318290fb73033f16ec996a45690c9596323679085a82734a24da44b04","first_computed_at":"2026-05-18T01:17:24.761281Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:17:24.761281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m60pxpfJl+ymNY7tKPVq9kSspZLPgULsF2/F8jYxJqYhqfhNMcHNWfUfIs/s1AmZ5RFFANm1Q8lcldiRzKraAw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:17:24.761782Z","signed_message":"canonical_sha256_bytes"},"source_id":"1601.04149","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b3f168d306f0511ae95ef59847c286f92d1c81ce3599b0f0a7cd14aa2493162","sha256:7329158d3b904de36205eca822bab862ff8e2469c3e1fe87ec62e260372f9b6e"],"state_sha256":"028be9be5f7d7612f4fe580db307b1a50f82f103423d0086b3d612a55e0b8fda"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uEhWweGK+tVqeEZVQWEFbX5XftUlidkhYZHfS0Nb1GHyJTe0zqc3oHibCmAT8NZ8oUWIMleSAC+DV9fkc6B6Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T03:37:28.276467Z","bundle_sha256":"5d9513b8cb3bc9f4068f9767bf02cd1c73bc7a120b351ccad725d102cc2ec425"}}